Edge classification using photo-geometric features
暂无分享,去创建一个
[1] P. Fua,et al. Pose estimation for category specific multiview object localization , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[2] Vincent Lepetit,et al. Pose estimation for category specific multiview object localization , 2009, CVPR.
[3] Alexei A. Efros,et al. Estimating natural illumination from a single outdoor image , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[4] Jiri Matas,et al. On Combining Classifiers , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[5] Arnold W. M. Smeulders,et al. c ○ 2005 Springer Science + Business Media, Inc. Manufactured in The Netherlands. A Six-Stimulus Theory for Stochastic Texture , 2002 .
[6] Edward H. Adelson,et al. Recovering intrinsic images from a single image , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[7] W. Marsden. I and J , 2012 .
[8] G LoweDavid,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004 .
[9] Joost van de Weijer,et al. Physics-based edge evaluation for improved color constancy , 2009, CVPR.
[10] Theo Gevers,et al. Classifying color edges in video into shadow-geometry, highlight, or material transitions , 2003, IEEE Trans. Multim..
[11] Theo Gevers,et al. Shadow edge detection using geometric and photometric features , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).
[12] Cordelia Schmid,et al. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[13] Koen E. A. van de Sande,et al. Evaluating Color Descriptors for Object and Scene Recognition , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[14] Joost van de Weijer,et al. Edge and corner detection by photometric quasi-invariants , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[15] G D Finlayson,et al. Color constancy at a pixel. , 2001, Journal of the Optical Society of America. A, Optics, image science, and vision.